The present invention generally relates to an apparatus and methodology for monitoring and reporting acoustic levels, and more specifically to a system for monitoring and reporting sound levels in an area in order to control noise in that area.
The present system is a sound monitoring, data collection, and advisory system that provides empirical data and can provide visual cues to empower and facilitate un-biased control over noise levels. This enables a facility to maintain a desired acoustic level for employees, visitors, patients and/or others. The system's flexibility can meet any client's current needs and makes future system expansion easy and cost-effective. The system monitors the ambient noise level in the monitored area, collects data on characteristics of the noise, and provides a visual representation of the noise level. The system could be installed in environments that include, but are not limited to, hospital intensive care units, standard patient care areas (e.g. patient rooms), schools, libraries, museums, industrial facilities, sleep centers, academia, high security areas as a component of high-end security systems, or anywhere else sound control is desired.
Excessive noise can compromise a newborn's well-being and negatively impact an infant's growth and development. For these reasons, it is especially important to control sound levels in a neo-natal intensive care unit (NICU). The present system facilitates compliance with developing NICU noise control standards, and can be reconfigured easily as those standards evolve. The medical industry in general, and NICU's in particular, are experiencing rapid growth due to advances in technology and medical science. The NICU standard for noise control has evolved and matured over the last several years. More is known by doctors, nurses, specialists, and educators about the effects of excessive noise on infants in NICU's and on other individuals. The science is telling in that most if not all indicators show an urgent need for hospitals to take sound control seriously.
Technology has progressed rapidly resulting in the steady infusion of new equipment making more and more ambient noise. Alarms, monitors and communication systems all contribute to the rise in ambient noise. As the ambient noise level rises, staff noises and voices also rise as they compete to be heard. This vicious cycle of rising sound levels can be detrimental to the living and working environment of people.
The sound level can be measured in decibels (dB), which is a logarithmic unit of measurement that expresses the magnitude of a physical quantity relative to a specified or implied reference level. The difference in decibels between the power of two sounds is 10 log10 (P2/P1) dB. Since it expresses a ratio of two quantities with the same units, it is a dimensionless quantity. When the decibel is used to give the sound level for a single sound rather than a ratio, then a reference level must be chosen. For sound intensity, the reference level (for air) is usually chosen as 20 micropascals, or 0.02 mPa, which is the threshold of human hearing, the lowest sound pressure level at which the human ear can detect sound. For acoustic (calibrated microphone) measurements, the response can be set such that 20 μPa=0 dB.
Not all sound pressures are equally loud. This is because the human ear does not respond equally to all frequencies. Loudness is not the same thing as sound intensity, and there is not a simple relationship between the two, because the human hearing system is more sensitive to some frequencies than others. Furthermore, the frequency response of the human hearing system varies with loudness, as has been demonstrated by the measurement of equal-loudness contours. Humans are more sensitive to sounds in the frequency range of about 1 kHz to 4 kHz than to lower or higher frequency sounds.
For these reasons, sound meters are often fitted with a filter that has a frequency response modeled to reduce the contribution of low and high frequencies in order to produce a reading which corresponds approximately to what we hear. A filter response commonly used to model human hearing is the A-weighting filter defined in the International standard IEC61672:2003. A-weighting is the most commonly used of a family of curves defined in IEC179 and various other standards relating to the measurement of perceived loudness, as opposed to actual sound intensity. A-weighted decibels are abbreviated dB(A) or dBA. When acoustic (calibrated microphone) measurements are being referred to, then the units used will be dB SPL (sound pressure level) referenced to 20 micropascals=0 dB SPL. A-weighting is also in common use for assessing potential hearing damage caused by loud noise. Although the threshold of hearing is typically around 0 dB SPL, most common appliances are likely to have noise levels of 30 to 40 dB SPL.
To better characterize the sound, an FFT (Fast Fourier Transform) may be performed. The Fourier transform is a method for reducing a sample of audio spectral content to a compact data set. These data sets can be stored and recalled and utilized as a method of describing acoustical events within an area with a minimum amount of data. This data set is comparable to a Bode magnitude plot and can support various levels of resolution, for example there can be 128 or 1024 data per set to describe an acoustic event.